The ultimate value of fundamental biological discoveries from the Center for Inflammatory Disorders will become apparent only when "downstream" interventions are implemented to control inflammation, thereby improving the health of patients and population. In this context, human health includes both extension of lifespan and enhancement of Quality of Life (QoL)-two objectives of the health care system enshrined in the Healthy People 2000 initiative. However, it is only recently that reliable and valid methods for measuring oral health related QoL have become widely available, with the consequence that methods for evaluate quality of life outcomes from oral health interventions remain in their infancy. One area that is important to this Center's mission is the potential for synergistic effects of local (oral) and systemic disease on human health, although there is a lack of methodological work to evaluate such joint effects with either disease specific (ie. oral health related QoL) or generic QoL instruments. The aim of this study is to evaluate methods that are optimal for measuring joint and synergistic effects on systemic conditions, oral disease and its treatment on quality of life. This study will measure oral health related QoL using the short form Oral Health Impact Profile (OHIP-14) and genetic QoL using the Medical Outcomes Study short-form health survey (SF-36). These questionnaires will be completed by 130 (terminal dentition) patients who have advanced dental disease and who have expressed an intent for ultimate removal of those teeth and placement with complete dentures. QoL measures will be administered at baseline, 4 weeks, 26 weeks and 52 weeks, and concurrent treatments and clinical status will be abstracted from treatment records. The data will be analyzed for psychometric independence of oral and generic QoL. Specific aims will be explored initially through cross- sectional analyses, where QoL measures will be the dependent variables and oral status (aim 1) or dental treatments (aim 2) will be the dependent variables. our study hypotheses will then be analyzed using longitudinal data analyzed using repeated measures of variance.